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Paper Citation Record · LEDGER

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models

As of 8 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2606.24152.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2606.24152 v2

Coverage vector

measured 26 of 26 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-02T10:25:06.087772Z

measured 26 of 26 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

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26 of 26 outbound references displayed

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Outbound references

Observation 52c1fa55-d3f2-4373-a566-b7166fcf854f · outbound

This paper cites Video generation models as world simulators.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Video generation models as world simulators

Reference 1

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Observation 11d9b139-dee3-44ed-ae82-d55a354799ab · outbound

This paper cites A note on the eval- uation of generative models.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models A note on the eval- uation of generative models

Reference 2

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Observation 0be3173d-557d-4f40-be52-19c74619c709 · outbound

This paper cites Improved preci- sion and recall metric for assessing generative models.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Improved preci- sion and recall metric for assessing generative models

Reference 3

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Observation d9aad5cd-30e8-41c4-9edd-eb1307bec5f9 · outbound

This paper cites The unreasonable effec- tiveness of deep features as a perceptual metric.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models The unreasonable effec- tiveness of deep features as a perceptual metric

Reference 4

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Observation 6d86fb87-f0e7-44a1-8a19-080b0858d50e · outbound

This paper cites Towards Accurate Generative Models of Video: A New Metric & Challenges.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 5

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Observation 9be8a540-27a6-41de-b4ca-53ac9c3f2b42 · outbound

This paper cites VBench: comprehensive bench- mark suite for video generative models.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models VBench: comprehensive bench- mark suite for video generative models

Reference 6

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Observation c67682b1-d88f-4591-8e6b-f2c6e4b1028c · outbound

This paper cites Recurrent world models facili- tate policy evolution.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Recurrent world models facili- tate policy evolution

Reference 7

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Observation 39115c03-63ac-4d09-93df-c9bc3e3ff2ba · outbound

This paper cites Learning latent dynam- ics for planning from pixels.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Learning latent dynam- ics for planning from pixels

Reference 8

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Observation ab8a2940-89a7-4496-8344-c5d4c7a7008e · outbound

This paper cites Mastering di- verse control tasks through world models.Nature2025; 640: 647–653.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Mastering di- verse control tasks through world models.Nature2025; 640: 647–653

Reference 9

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Observation ca1971a6-5af4-4a8f-8f69-79c464868f88 · outbound

This paper cites RT -2: Vision-language-action models transfer web knowledge to robotic control.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models RT -2: Vision-language-action models transfer web knowledge to robotic control

Reference 10

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Observation c36c90a9-7fc9-4204-9025-a42b0b6a256e · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 11

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Observation a1ec670d-ca14-47b7-b75f-991ca6b8659b · outbound

This paper cites VIMA: General robot ma- nipulation with multimodal prompts.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models VIMA: General robot ma- nipulation with multimodal prompts

Reference 12

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Observation 2d7413b2-7f8c-4766-bd40-f67c0451030f · outbound

This paper cites Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Reference 13

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Observation e0b1cc6a-c629-4b4d-b212-b74c557cbdf4 · outbound

This paper cites Diffusion policy: visuomotor policy learning via action diffusion.Int J Robot Res2025; doi:10.1177/02783649241273668.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Diffusion policy: visuomotor policy learning via action diffusion.Int J Robot Res2025; doi:10.1177/02783649241273668

Reference 14

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Observation 52066578-b785-4ee9-b1a4-b111908566e0 · outbound

This paper cites Learning to simulate complex physics with graph networks.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Learning to simulate complex physics with graph networks

Reference 15

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Observation fa89494b-534a-46ef-b028-1382361dfb83 · outbound

This paper cites Genie: generative interactive environments.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Genie: generative interactive environments

Reference 16

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Observation 423878ee-75a5-41ea-9c63-1e24782f9750 · outbound

This paper cites Learning interactive real-world simulators.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Learning interactive real-world simulators

Reference 17

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Observation 09b03af5-c89c-4a71-9770-9d2c66bb036b · outbound

This paper cites Cosmos World Foundation Model Platform for Physical AI.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Cosmos World Foundation Model Platform for Physical AI

Reference 18

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Observation c77664c3-bdf7-41ea-9e33-a301e02cf4a4 · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 19

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Observation d70c5deb-8c30-4726-bb3f-eefbcf457bc5 · outbound

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Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Unresolved cited work

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Observation 1ae3255e-c6d2-4e37-a3d8-6e78a1dbb494 · outbound

This paper cites The Essential Role of Causality in Foundation World Models for Embodied AI.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models The Essential Role of Causality in Foundation World Models for Embodied AI

Reference 21

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Observation 350d0758-cb85-4179-a442-322be0bf657a · outbound

This paper cites Benchmarking neural net- work robustness to common corruptions and perturbations.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Benchmarking neural net- work robustness to common corruptions and perturbations

Reference 22

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Observation f4a44fef-26c4-413f-b604-9db30fd81470 · outbound

This paper cites WILDS: a bench- mark of in-the-wild distribution shifts.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models WILDS: a bench- mark of in-the-wild distribution shifts

Reference 23

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Observation b0d712f9-d2ac-40c9-bda7-897a1d10c000 · outbound

This paper cites Can you trust your model’s uncertainty? Evaluating predictive uncertainty un- der dataset shift.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Can you trust your model’s uncertainty? Evaluating predictive uncertainty un- der dataset shift

Reference 24

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Observation aa759f7b-fb2b-4516-85f3-a007743e3630 · outbound

This paper cites Control barrier functions: theory and applications.

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Control barrier functions: theory and applications

Reference 25

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Observation 4ea7daac-6419-4473-b5bc-18d5426868c6 · outbound

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Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models Unresolved cited work

Reference 2024

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